At the end of February 2026, the results of the TAČR SIGMA competition were announced, in which only four projects out of nineteen were successful. Among the supported projects is the National Centre for Artificial Intelligence (NCUI), led by Assoc. Prof. Přemysl Šůcha, Ph.D. As of March 1, 2026, he also heads the Department of Industrial Informatics, where he succeeded Prof. Zdeněk Hanzálek, who is now focusing on leading the Optimization team and the OP JAK ROBOPROX project—an equally significant initiative with a stronger focus on fundamental research.
The Department of Industrial Informatics has long positioned itself as a workplace with strong real-world impact. It delivers projects with direct industrial applications, receives prestigious awards, and achieves above-average results in the national evaluation of research organizations. “For example, in Methodology 17+, our department achieves better results in applied outcomes than some entire faculties,” notes Přemysl Šůcha in the interview. The discussion highlights that success is not driven only by advanced algorithms, but mainly by a focus on real-world needs—from managing hybrid power plants to healthcare and defense. It also emphasizes the importance of strengthening the department’s role as a bridge between research and industry, both nationally and internationally.
Šůcha sees closer collaboration between academia and industry as essential: “Effective cooperation between academia and industry in the Czech Republic is lacking. I see shortcomings on both sides, but we need to find solutions.”
Read the interview below for an inside look at cutting-edge research, along with an open reflection on why innovation in the Czech Republic progresses more slowly than it could.
Your field falls under industrial informatics. How would you explain it to someone outside the field?
We develop specialized algorithms for complex, non-trivial problems. This often includes optimization of complicated processes, decision-support methods, simulation of complex systems, and control of autonomous vehicles. Our scope is broad, covering industrial production, automotive, energy, healthcare, business processes, and defense systems.
What trends are shaping industrial informatics today—and which are truly fundamental rather than just hype?
From our perspective, the key trend is digitalization. If a problem is not digitized, it is difficult to optimize or innovate, because every algorithm needs data. Today’s society is heavily focused on machine learning and artificial intelligence, but these methods require high-quality digital data. Without it, their application is very limited.
Unfortunately, digitalization often lags behind. This is especially visible in healthcare. I’ve worked with many doctors, for example on scheduling surgical operations, and it is surprising how poor or incomplete the data often is.
What is your team currently working on?
We work across multiple domains, with current focus on energy, healthcare, and defense.
For example, we recently completed a control algorithm for a hybrid power plant by Energy Nest, which has been successfully operating for over a year in Vraňany. The control system received a Siemens award, and the project itself also earned recognition.
We are now working on algorithms to improve passive radar systems and to optimize the digitalization of business processes, for example in banking. Both are nearing integration into final products.
At the same time, we are developing new opportunities in healthcare and manufacturing. Since March, we have also been involved in the National Centre for Artificial Intelligence project, which I lead. I am pleased that my deputy in this project is Assoc. Prof. Tomáš Kroupa from FEL CTU.
Can you briefly introduce the National Centre for Artificial Intelligence project?
The project connects six academic institutions, more than thirty industrial partners, and public administration bodies. Its goal is to develop innovative AI methods with real-world applications.
The project is overseen by a board including leading figures such as Prof. Vladimír Mařík, Prof. Michal Pěchouček, Jan Kavalírek, and Lukáš Kačena. A strong emphasis is placed on sharing knowledge across disciplines—from IT and energy to security, healthcare, robotics, and autonomous systems.
We have assembled top experts, and I am looking forward to the results. It will be an intensive six-year effort.
What does the typical journey of a project look like—from idea to real-world deployment?
Every successful project depends on people willing to drive change. We start with a thorough analysis of the problem—understanding the process, identifying improvement opportunities, and defining real user needs.
We then prepare a specification and begin with a short feasibility study to assess complexity and economic return. The project is implemented either as a contract or through funding calls.
We work closely with the industrial partner until testing is complete. Commercialization and maintenance are then handled by the partner.
How do expectations differ between industry and academia?
Each sector is different, but what matters most is whether partners truly want change.
Companies often view universities as service providers expecting complete software solutions, including maintenance—or they seek cheaper versions of existing tools. However, our strength lies in designing innovative solutions and prototypes.
We bring expertise in optimization and advanced AI algorithms that companies typically do not have. We are not database administrators or web developers.
In general, collaboration between companies and academia in the Czech Republic still does not work well. Companies often lack ambition and courage for innovation. Many initiatives remain at the PowerPoint stage or stop when approval is needed from foreign headquarters. Another barrier is reluctance to share process data.
How do you use AI in your work, and when is classical mathematical optimization more suitable?
It depends on the application. In some cases, AI provides major benefits; in others, pure mathematical approaches are more effective.
The term “artificial intelligence” itself is often overused—both by companies and researchers. It’s a very broad concept, and we need to treat it carefully.
What will be the key topic in industrial informatics over the next 5–10 years?
Digitalization will remain crucial. There is still more talk than action.
At the same time, software development may change significantly. Instead of traditional programming, we may generate software from technical specifications. This raises important questions about reliability and safety, which are not yet fully answered.
What are the main challenges in energy today?
The energy sector is changing rapidly. New technologies require more complex control systems and greater efficiency, which creates opportunities for optimization algorithms.
However, every solution must be carefully evaluated. For example, we are currently working on a study for the Ministry of Industry and Trade on using electrolyzers for hydrogen production combined with grid balancing services. The viability of such technologies is not straightforward and must be assessed case by case.
Where do you see further opportunities?
Primarily in defense and healthcare.
Defense is driven by geopolitical developments, with countries like Poland investing heavily. If the Czech Republic wants to stay competitive, it must innovate.
Healthcare, on the other hand, suffers from inefficiencies. There is significant room for improvement in process management, and inspiration can often be drawn from industrial production.
Have you managed to make changes in healthcare?
Yes, but still far less than what is possible.
For example, we developed a digital twin of laboratory systems used for analyzing clinical samples. It is now used in Central Europe to design and configure laboratory systems.
Since every hospital is different, designing these systems is complex. Our goal is to extend the solution to automatically assign tests within the system, reducing turnaround time and operational costs.
If you could wish for one thing to support your department, what would it be?
I would like to see more companies willing to take risks and develop innovative solutions with us.
Change does not happen overnight. It requires people willing to engage and rethink established practices. Nothing kills innovation more than resistance to change.
I would also like to see more job opportunities for people capable of driving innovation. Recently, many of our graduates report doing routine work in companies, with little room for creativity, and are considering doctoral studies instead.
We talk a lot about AI, optimization, and digitalization—but real change is limited. If the Czech Republic wants to succeed, it must create its own solutions that can compete globally. Universities and research institutes like CIIRC can contribute—but we need courageous companies to make it happen.
